부산대학교 도서관

This article introduces a multimetric multiconstraint strategic path planning framework applicable to unstructured urban airspace. The planner is based on a modular and scalable approach to handle several information sources and aspects characterizing urban flight scenarios, such as risk and weather maps, landing site locations, navigation requirements, and mobile and fixed obstacle characteristics. This information is coupled with dynamic constraints and unmanned aerial vehicle specifications to derive a flyable and safe path connecting a start position and a destination. Strategies for data gathering and synthesis, used to keep a reduced computational burden, are described along with the path planner algorithm. The latter consists in three steps specifically developed to handle both static and time-varying information. A multi-objective cost function with variable weighting coefficients has been implemented so that the most relevant factors for the considered applications can be selected in an adaptive fashion. The performance of the developed algorithms is tested by investigating the planner behavior when changing its inputs as well as the cost function weighting coefficients, demonstrating the ability of the planner in returning an efficient and safe trajectory.